NVIDIA A100 SXM 80GB
The A100 80GB is the high-memory variant of NVIDIA's Ampere datacenter GPU with 80GB HBM2e. A proven workhorse for AI training and HPC workloads in cloud and enterprise deployments.
VRAM
80 GB
Memory
HBM2e
Bandwidth
2,039 GB/s
FP16
312 TF
TDP
400 W
Memory and compute
Architecture and power
Notes
High-memory variant
Models that may fit on NVIDIA A100 SXM 80GB
Estimates based on INT8 quantization. Actual fit depends on framework and batch size.
More GPUs by NVIDIA
The manufacturer's other cards in the catalog, largest memory first, with bandwidth and power where published.
Frequently asked questions about NVIDIA A100 SXM 80GB
Answered from the entry's own figures: memory, which models fit, bandwidth, power and the card's class.
NVIDIA A100 SXM 80GB has 80 GB of HBM2e at 2,039 GB/s. At INT8 a model's weights take about one byte per parameter, so the card holds roughly a 64B-parameter model with room for context; larger models need several cards or a lower precision.
From the catalog's estimates at INT8, Kimi Linear 48B A3B Base, Llama 3_3 Nemotron Super 49B V1, Gemma 4 31B IT and Llama Nemotron Embed Vl 1B V2 fit on a single NVIDIA A100 SXM 80GB with their default context. The list on this page shows the estimated memory each takes; the capacity planner sizes any model against this card for your own context length, batch size and request rate.
2,039 GB/s. Bandwidth bounds how fast a model generates tokens, because every token reads the whole set of weights and the KV cache from memory; at this rate a 64B model at INT8 could be read on the order of 32 times a second on one card, before batching and framework efficiency.
NVIDIA A100 SXM 80GB has a TDP of 400 W, with a maximum of 400 W, in the SXM4 form factor. Budget the TDP per card plus host overhead when sizing a server's power and cooling.
NVIDIA A100 SXM 80GB is a datacenter accelerator, meant for servers and multi-GPU serving, built on the Ampere architecture and released in 2020. It supports a multi-GPU interconnect at 600 GB/s, so a model larger than one card can be split across several.
Specifications from the manufacturer's published material; a figure that is not published is shown as such, and a derived one is explained in the notes.
Added Jan 25, 2026 · Last updated Jan 25, 2026
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